a eHEALS: eHealth Literacy Scale.
b All standardization factor loadings were positive and statistically significant.
c CR: composite reliability.
d AVE: average variance extracted.
e Not applicable.
Factors | Search | Usage | Evaluation |
Search | 0.909 | — | — |
Usage | 0.864 | 0.875 | — |
Evaluation | 0.792 | 0.823 | 0.843 |
b Square root of average variance extracted (AVE) for each factor.
c Not applicable.
Table 4 shows the sociodemographic variables in this study. In total, 406 students were enrolled in this study. Overall, 252 (62.1%) of the 406 participants were female, 224 (55.2%) lived with family members or friends, and 269 (66.3%) did not have specific religious beliefs. Regarding institution ownership and educational goals, the sample ratio was close to the distribution ratio of various universities in Taipei. More than half of the students were enrolled in private universities (n=226, 55.7%) than in public universities. Furthermore, the ratio of students attending general universities (n=227, 55.9%) was higher than that of students attending vocational colleges. Regarding the parental education level, 237 (58.4%) of the participants had fathers with a university degree or higher, while 252 (62.1%) had mothers with a university education level or higher. Most participants had a monthly disposable amount of NT $10,000 (US $308) or less (n=182, 44.8%). Additionally, a significant proportion of the participants spent less than 1 hour reading per day (n=198, 48.8%), while the majority spent 6 hours or more on mobile devices and computers daily (n=225, 55.4%). The participants indicated that their primary information-acquiring channel was self-searching (n=361, 88.9%), with only a minority (n=45, 11.1%) relying on asking others. Notably, 253 (62.3%) of the participants reported having a good perceived health status.
Characteristics | Participants, n (%) | |
Male | 154 (37.9) | |
Female | 252 (62.1) | |
Public | 180 (44.3) | |
Private | 226 (55.7) | |
General university | 227 (55.9) | |
Vocational college | 179 (44.1) | |
With others | 224 (55.2) | |
Alone | 182 (44.8) | |
High school or lower | 169 (41.6) | |
University or higher | 237 (58.4) | |
High school or lower | 154 (37.9) | |
University or higher | 252 (62.1) | |
Without | 269 (66.3) | |
With | 137 (33.7) | |
≤10,000 (≤US $308) | 182 (44.8) | |
10,001-15,000 (US $308-$462) | 137 (33.8) | |
≥15,001 (≥US $462) | 87 (21.4) | |
<1 | 198 (48.8) | |
1.0-2.9 | 159 (39.1) | |
≥3 | 49 (12.1) | |
<3 | 44 (10.8) | |
3.0-5.9 | 137 (33.8) | |
≥6 | 225 (55.4) | |
Consulting others | 45 (11.1) | |
Self-searching | 361 (88.9) | |
Good | 253 (62.3) | |
Average | 134 (33.0) | |
Poor | 19 (4.7) |
a An exchange rate of NT $1=US $0.03 was used.
In eHEALS, the mean total score was 3.17 (SD 0.48). The score of the usage subscale was the highest (mean 3.25, SD 0.50), followed by the search subscale (mean 3.20, SD 0.52) and the evaluation subscale (mean 3.08, SD 0.56). In the HPLP, the mean total score was 3.55 (SD 0.62). The score of the interpersonal support subscale was the highest (mean 3.87, SD 0.70), followed by the self-actualization subscale (mean 3.85, SD 0.74), the stress management subscale (mean 3.74, SD 0.74), the nutrition subscale (mean 3.41, SD 0.79), and the health responsibility subscale (mean 3.26, SD 0.87), with the exercise subscale (mean 3.18, SD 0.90) being the lowest.
As shown in Table 5 , the total HPLP score showed significant differences between sexes ( t 404 =2.346, P =.02), institution orientation ( t 404 =2.564, P =.01), daily reading time ( F 2,403 =17.618, P <.001), daily screen time ( F 2,403 =7.148, P <.001), primary information channel ( t 404 =3.892, P <.001), and perceived health status ( F 2,403 =24.366, P <.001). Specifically, the HPLP score was higher for male participants (mean 3.65, SD 0.71) than female ones (mean 3.49, SD 0.55). Participants attending general university (mean 3.62, SD 0.59) had a higher HPLP score than those attending vocational college (mean 3.46, SD 0.65). Regarding daily reading time, participants who read for 1.0-2.9 (mean 3.67, SD 0.58) and ≥3 hours (mean 3.87, SD 0.49) had higher HPLP scores than those who read for <1 hour (mean 3.38, SD 0.64). Regarding daily screen time, participants who spent <3 hours (mean 3.70, SD 0.61) had higher HPLP scores than those who spent ≥6 hours (mean 3.45, SD 0.60). Additionally, the HPLP score was higher for participants who acquired information from others (mean 3.89, SD 0.59) than those who acquired information by themselves (mean 3.51, SD 0.62). Participants with a good perceived health status (mean 3.71, SD 0.62) had higher HPLP scores than those with an average (mean 3.32, SD 0.55) or a poor (mean 3.09, SD 0.50) perceived health status.
Stepwise multiple linear regression was performed to analyze sociodemographic variables that affected the HPLP of participants ( Table 6 ). Results showed that sex, institution orientation, daily reading time, primary information channel, and perceived health status are confounders of the overall HPLP. In particular, male participants, participants attending general university, those who read for ≥1 hour daily, those who acquired information from others, and those with a good perceived health status had a better HPLP. Collinearity was absent between the independent variables (tolerance=0.825-0.969, VIF=1.032-1.212), and the factors explained 19.8% of the variance (adjusted R 2 =0.198, F 7,398 =15.290, P <.001).
Characteristics | HPLP, mean (SD) | |
=.02 ) | ||
Male | 3.65 (0.71) | |
Female | 3.49 (0.55) | |
=.01) | ||
General university | 3.62 (0.59) | |
Vocational college | 3.46 (0.65) | |
<.001) | ||
<1 hour | 3.38 (0.64) | |
1.0-2.9 hours | 3.67 (0.58) | |
≥3 hours | 3.87 (0.49) | |
<.001) | ||
<3 hours | 3.70 (0.61) | |
3.0-5.9 hours | 3.67 (0.64) | |
≥6 hours | 3.45 (0.60) | |
<.001) | ||
Consulting others | 3.89 (0.59) | |
Self-searching | 3.51 (0.62) | |
<.001) | ||
Good | 3.71 (0.62) | |
Average | 3.32 (0.55) | |
Poor | 3.09 (0.50) |
a HPLP: health-promoting lifestyle profile.
b From an independent sample 2-tailed t test for comparing dichotomized variables.
c From 1-way ANOVA combined with the Scheffé post hoc test for comparing variables with more than 2 categories.
d,e Values with different superscript letters in variables with more than 2 categories indicate significant differences by Scheffé post hoc test.
Factors | B | β | value | Tolerance | VIF | |
Male | 0.159 | 0.124 | .007 | 0.958 | 1.044 | |
General university | 0.126 | 0.101 | .03 | 0.940 | 1.064 | |
1.0-2.9 | 0.249 | 0.195 | <.001 | 0.905 | 1.104 | |
≥3 | 0.319 | 0.167 | <.001 | 0.825 | 1.212 | |
Consulting others | 0.279 | 0.141 | .002 | 0.932 | 1.073 | |
Average | –0.345 | –0.261 | <.001 | 0.969 | 1.032 | |
Poor | –0.548 | –0.186 | <.001 | 0.967 | 1.034 |
b VIF: variance inflation factor.
Pearson product-moment correlation was performed to analyze the correlation between eHEALS and the HPLP ( Table 7 ). The overall eHEALS showed a significantly moderate positive correlation with the overall HPLP among participants ( r =0.512, P <.001). Furthermore, different eHEALS dimensions showed a significantly low-to-moderate positive correlation with the various HPLP dimensions ( r =0.291-0.522, P <.001).
Binary logistic regression was performed to analyze the predictive effects of the overall eHEALS and its various dimensions on the overall HPLP among participants ( Table 8 ). After adjusting for sociodemographic variables, compared with participants with relatively high overall eHEALS scores, those with relatively low eHEALS scores had 3.37 times the risk of a negative HPLP (adjusted odds ratio [OR]=3.37, 95% CI 1.49-7.61). The model exhibited a good fit (Hosmer-Lemeshow χ 2 8 =2.128, P =.98), could explain 14.7%-24.4% of the variance (Cox-Snell R 2 =0.147, Nagelkerke R 2 =0.244), and had an accurate classification rate of 83.3%.
HPLP items | eHEALS | |||||||||
Overall scale | Search subscale | Usage subscale | Evaluation subscale | |||||||
r | value | r | value | r | value | r | value | |||
Overall | 0.512 | <.001 | 0.442 | <.001 | 0.406 | <.001 | 0.521 | <.001 | ||
Self-actualization | 0.395 | <.001 | 0.375 | <.001 | 0.328 | <.001 | 0.363 | <.001 | ||
Health responsibility | 0.481 | <.001 | 0.410 | <.001 | 0.336 | <.001 | 0.522 | <.001 | ||
Exercise | 0.375 | <.001 | 0.311 | <.001 | 0.291 | <.001 | 0.397 | <.001 | ||
Nutrition | 0.411 | <.001 | 0.359 | <.001 | 0.326 | <.001 | 0.416 | <.001 | ||
Interpersonal support | 0.348 | <.001 | 0.299 | <.001 | 0.306 | <.001 | 0.338 | <.001 | ||
Stress management | 0.397 | <.001 | 0.327 | <.001 | 0.336 | <.001 | 0.406 | <.001 |
b HPLP: health-promoting lifestyle profile.
eHEALS items | HPLP | Unadjusted | Adjusted | |||||||
Positive | Negative | OR (95% CI) | value | OR (95% CI) | value | Model value | ||||
Relatively low | 218 | 62 | 4.20 (1.94-9.06) | <.001 | 3.37 (1.49-7.61) | .004 | <.001 | |||
Relatively high (reference) | 118 | 8 | — | — | — | — | — | |||
Relatively low | 216 | 61 | 3.77 (1.81-7.85) | <.001 | 3.38 (1.54-7.42) | .002 | <.001 | |||
Relatively high (reference) | 120 | 9 | — | — | — | — | — | |||
Relatively low | 216 | 58 | 2.69 (1.39-5.20) | .003 | 2.25 (1.11-4.59) | .025 | <.001 | |||
Relatively high (reference) | 120 | 12 | — | — | — | — | — | |||
Relatively low | 233 | 63 | 3.98 (1.76-8.98) | <.001 | 3.20 (1.35-7.59) | .008 | <.001 | |||
Relatively high (reference) | 103 | 7 | — | — | — | — | — |
c Adjusted for sex, institution orientation, daily reading time, daily screen time, primary information channel, and perceived health status.
d OR: odds ratio.
Compared with participants with relatively high eHEALS search subscale scores, those with relatively low search abilities had 3.38 times the risk of a negative overall HPLP (adjusted OR=3.38, 95% CI 1.54-7.42). The model exhibited a good fit (Hosmer-Lemeshow χ 2 8 =3.052, P =.93), could explain 14.8%-24.7% of the variance (Cox-Snell R 2 =0.148, Nagelkerke R 2 =0.247), and had an accurate classification rate of 83.3%. Compared with participants with relatively high eHEALS usage subscale scores, those with relatively low usage abilities had 2.25 times the risk of a negative HPLP (adjusted OR=2.25, 95% CI 1.11-4.59). The model exhibited a good fit (Hosmer-Lemeshow χ 2 8 =10.538, P =.23), could explain 13.7%-22.8% of the variance (Cox-Snell R 2 =0.137, Nagelkerke R 2 =0.228), and had an accurate classification rate of 82.8%. Moreover, compared with participants with relatively high eHEALS evaluation subscale scores, those with relatively low evaluation abilities had 3.20 times the risk of a negative HPLP (adjusted OR=3.20, 95% CI 1.35-7.59). The model exhibited a good fit (Hosmer-Lemeshow χ 2 8 =2.916, P =.94), could explain 14.3%-23.8% of the variance (Cox-Snell R 2 =0.143, Nagelkerke R 2 =0.238), and had an accurate classification rate of 83.7%.
Further analysis of the prediction results of eHEALS on various dimensions of the HPLP was conducted ( Multimedia Appendix 3 ). Results showed that compared with participants with relatively high overall eHEALS scores, those with relatively low eHEALS scores had 2.74 times the risk of negative health responsibility (adjusted OR=2.74, 95% CI 1.55-4.84), 2.41 times the risk of negative exercise (adjusted OR=2.41, 95% CI 1.43-4.07), and 1.86 times the risk of negative nutrition (adjusted OR=1.86, 95% CI 1.07-3.22).
Compared with participants with relatively high eHEALS subscales scores, those with relatively low search, usage, and evaluation abilities, respectively, had 2.66 (adjusted OR=2.66, 95% CI 1.52-4.62), 2.00 (adjusted OR=2.00, 95% CI 1.18-3.37), and 3.01 (adjusted OR=3.01, 95% CI 1.63-5.55) times the risk of negative health responsibility; 2.02 (adjusted OR=2.02, 95% CI 1.22-3.35), 2.12 (adjusted OR=2.12, 95% CI 1.29-3.50), and 2.71 (adjusted OR=2.71, 95% CI 1.54-4.76) times the risk of negative exercise; and 2.08 (adjusted OR=2.08, 95% CI 1.12-3.86), 1.83 (adjusted OR=1.83, 95% CI 1.08-3.11), and 2.08 (adjusted OR=2.08, 95% CI 1.07-4.06) times the risk of negative nutrition. In addition, compared with participants with relatively high eHEALS evaluation subscale scores, those with relatively low evaluation abilities had 2.06 times the risk of negative stress management (adjusted OR=2.06, 95% CI 1.01-4.22).
Comparison of the chinese eheals 3-factor model with previous studies.
Norman and Skinner [ 15 ] developed eHEALS and highlighted that men’s eHEALS scores are significantly higher than those of women, which could be used as an a priori hypothesis. Similar results were obtained by using the Chinese eHEALS in this study; in other words, significant differences were observed in eHEALS scores between sexes ( t 404 =2.708, P =.007), with males having higher scores (mean 3.25, SD 0.51) than females (mean 3.12, SD 0.46). This shows that the Chinese eHEALS has known-groups validity. Moreover, in this study, the original 8 eHEALS questions were classified into 3 factors, namely search (questions 1-3), usage (questions 4 and 5), and evaluation (questions 6-8). Compared with the initial 1-factor model [ 15 ], CFA showed that the 3-factor model exhibits a better fit and good validity and reliability. The findings were similar to those of a recent study on the Chinese eHEALS multifactorial model [ 22 ]; however, this study showed more robust evidence of fit, validity, and reliability. In contrast to Sudbury-Riley et al [ 21 ], who used a 3-factor eHEALS model and defined question 3 as “I know how to find helpful health resources and information on the internet” and questions 4 and 5 as the ability to acquire and use health resources and information, this study defined questions 1-3 as the ability to search for health resources on the internet and questions 4 and 5 as the ability to use online health information. Results revealed that differences in the delineation of questions lead to variations in the model fit. Notably, empirical data showed that the fit of the 3-factor model in this study is superior to that of Sudbury-Riley et al’s [ 21 ] model. This can be attributed to 2 potential explanations. First, EFA was performed in the pretest to delineate the 3 factors, which differed from Sudbury-Riley et al’s [ 21 ] method, who carefully reviewed and partitioned the factors based on social cognitive and self-efficacy theories. Second, minor differences in participants’ perceptions of the translated scale may have contributed to these disparities [ 43 ]. In the English eHEALS, questions 3-5 start with “I know how to,” which may have caused participants to perceive them as belonging to the same factor [ 21 ]. In the Chinese eHEALS, participants tended to consider questions 1-3 as search factors due to words such as “what,” “where,” and “find,” while the word “use” in questions 4 and 5 led participants to classify it as a usage factor. Nonetheless, the 3-factor model used in this study complies with the foundational theories of the eHEALS lily model (ie, social cognitive theory and self-efficacy theory) [ 11 , 21 ]. This model may be more suitable for regions where the Chinese eHEALS is used in eHealth literacy studies.
In this study, the overall eHEALS score of the university students was moderate or higher, and the search and usage dimensions had higher scores. In contrast, the evaluation dimension had a lower score. This reveals that students perceive themselves to have good search and usage capabilities of eHealth information; however, they possess low confidence in evaluating such information and using it for decision-making. In recent studies, the mean scores for eHEALS questions 6-8 were lower than those for questions 1-3 and questions 4 and 5 [ 3 , 21 , 44 , 45 ], similar to scores obtained in this study. A Taiwanese study used a self-formulated scale to evaluate the eHealth literacy of university students and divided the questions into functional, interactive, and critical literacies [ 17 ]. Interactive literacy encompasses the ability to select, comprehend, and use online health information, which was similar to the search and usage dimensions in this study. Critical literacy refers to the ability to analyze, criticize, and respond to online health information, which was similar to the evaluation dimension in this study. The score for critical literacy was visibly lower than that for interactive literacy in the previous study [ 17 ], which was similar to this study. Researchers found that although most university students mentioned that they can understand the general idea of online health information, they have a vague understanding of the jargon, foreign languages, and data [ 6 ]. In addition, some university students lack confidence in the quality of online health information and express difficulty in determining the quality of such information [ 3 ]. Therefore, in the contemporary landscape characterized by the unlimited accumulation and dissemination of internet-based health information of uncertain veracity, imparting fundamental health knowledge to Taiwanese university students is imperative. This includes fostering a sense of caution toward eHealth information among students and equipping them with the ability to critically assess and validate uncertainties.
The overall HPLP of university students in this study was moderate or higher, wherein interpersonal support and self-actualization scores were the highest, while nutrition, exercise, and health responsibility scores were the lowest, similar to those of the most recent studies [ 46 - 49 ]. Among sociodemographic variables, stepwise multiple linear regression showed that female students, students attending vocational colleges, those with a daily reading time of <1 hour, those who acquired information by themselves, and those with an average or a poor perceived health status were confounders of a poor overall HPLP. This was consistent with the significant differences in the overall HPLP in these sociodemographic variables. Recent studies have found that sex affects the HPLP and health behaviors, such as exercise and sleep [ 17 , 48 , 49 ]. The frequency of discussions of health problems with others has been highlighted to positively affect the dietary behavior of university students [ 23 ]. Individuals with a good perceived health status or great concern for health have a better HPLP and show several health behaviors, such as eating, exercise, and sleep [ 17 , 23 , 24 , 47 , 49 ].
In addition, this study found that a daily reading time of ≥1 hour is a confounder of a good HPLP among university students. This may be because information in books, newspapers, and magazines usually undergoes review and proofreading, and reading more accurate and reliable hardcopy information may lead to a tendency to adopt a positive lifestyle profile. Some studies have highlighted that reading hardcopy materials can promote better comprehension results than reading from screens [ 50 , 51 ]. However, the increased screen time on digital media today has greatly decreased the reading time in print. In this study, only 208 (51.2%) of 406 university students read for ≥1 hour per day, but 362 (89.2%) spent ≥3 hours on mobile devices or computers daily. Recent studies have shown that newspapers and magazines are the media that Taiwanese university students spend the least time on, far below the time spent on mobile devices and computers [ 22 ]. Furthermore, mobile devices and computers have diverse online functions. The TWNIC survey found that the most commonly used internet functions among generation Z are real-time messaging, social networks, free videos, online news, online games, and ecommerce; however, online learning is not their priority [ 1 ]. In the ANOVA in this study, the HPLP score of participants with a daily screen time of ≥6 hours was significantly low. However, multiple linear regression excluded the daily screen time from the HPLP confounders. It is believed that frequent usage of mobile devices and computers by university students consumes the time spent on reading. Therefore, the effect of screen time in the multiple linear regression may be explained by the reading time factor. In the binary logistic regression in this study, daily screen time was still considered a confounder of HPLP scores.
After adjusting for sociodemographic factors that may affect the HPLP, this study revealed that eHEALS consistently and significantly affects the HPLP of university students. Compared with students with relatively high overall eHEALS scores, those with relatively low eHEALS scores had a higher probability of a negative overall HPLP, similar to the results of studies in other regions [ 4 , 25 ]. Other researchers have used their own created scales to measure eHealth literacy and proved that it predicts multiple HPLP dimensions in university students [ 24 ]. Many studies have found that eHealth literacy has positive effects on exercise, diet, and sleep behaviors [ 13 , 17 , 18 , 23 ], or even safe sex practice [ 13 ] and COVID-19 prevention [ 46 ] among university students. This study found that among the various HPLP dimensions, compared with a relatively high overall eHEALS score, a relatively low eHEALS score is associated with negative health responsibility, exercise, and nutrition. University students in this study had low HPLP health responsibility, exercise, and nutrition scores—dimensions that require improvements. At the same time, many recent studies have found that these health behaviors are poor in university students [ 46 - 49 ]. Additionally, among the 3 eHEALS dimensions in this study, compared with participants with relatively high search, usage, and evaluation literacies, those with relatively low scores had a higher probability of a negative overall HPLP and its health responsibility, exercise, and nutrition dimensions, similar to the overall eHEALS results. Regarding evaluation literacy, this study found that in addition to predicting the negative health responsibility, exercise, and nutrition dimensions of the HPLP, a relatively low eHEALS evaluation score can also reflect poor stress management. This result is similar to that of a recent study indicating that critical eHealth literacy can predict more HPLP dimensions [ 24 ].
This study has certain limitations, which can provide a reference for future studies. First, this study included only university students without major diseases from the capital of Taiwan, and the results can only be generalized to the eHealth literacy and health-promoting lifestyle of this population. It is recommended that future studies extend to other regions in Taiwan or university students with other health statuses. Second, some variables may be related to eHealth literacy and a health-promoting lifestyle, such as majors and health risk behaviors, and it is recommended that future studies expand to include these variables. In addition, although participants were advised that the entire process was anonymized, the self-administered questionnaire may have caused their answers to be exposed to memory recall errors, environmental effects, and social desirability bias. Lastly, a cross-sectional study design was used in this study, and the causal relationship between eHealth literacy and a health-promoting lifestyle, as well as changes in these 2 factors with time, could not be confirmed. Hence, further repeated-measures or longitudinal studies are required for clarification.
Nonetheless, this study confirmed the feasibility of using the Chinese version of the eHEALS 3-factor model to examine eHealth literacy and highlighted that eHealth literacy affects and predicts the HPLP in university students. In the contemporary world where internet use is widespread and portable mobile devices are rapidly advancing, using the internet, mobile phones, tablets, or computers as aids in daily life has become an unstoppable trend. If university students can cultivate the online learning habit early on and establish the concept of consulting to acquire information and reading in print, actively nurturing their skills to search, use, and access internet-based health information, it will undoubtedly positively impact their health-promoting behavior and lifestyle.
This study is the first to validate the Chinese eHEALS 3-factor model, encompassing search, usage, and evaluation dimensions. Notably, eHEALS is the first eHealth literacy measurement tool to be developed and is the most widely used. This 3-factor model results in more definite eHEALS content and undoubtedly increases the practicality and applicability of the scale to satisfy the eHealth literacy evaluation needs of health promoting–related studies, particularly in Chinese-speaking regions.
Higher education represents the most significant and final opportunity for behavioral development and learning in young people. Behavioral health during this period impacts lifetime health outcomes. This study found that alongside specific sociodemographic characteristics, the overall eHEALS and its dimensions are independent predictors of the HPLP. Compared to university students with relatively high overall eHEALS and various dimension scores, those with relatively low scores had a negative overall HPLP and HPLP health responsibility, exercise, and nutrition. University students with relatively low eHEALS evaluation scores compared to those with relatively high evaluation scores also had negative stress management. These findings can be used to screen university students who require HPLP improvement so that health education suitable for their needs can be provided.
In addition, there is room for improving overall eHEALS scores among university students, with particular attention to improving evaluation literacy. It is recommended that the centers for general education, digital learning, and health of the universities and colleges in Taipei, as well as targeting populations with relatively low eHealth literacy (eHEALS score<3.17), be integrated to provide appropriate health education and programs. Courses should be conducted to educate students on identifying objective, credible, and understandable online health information platforms, while cultivating vigilance and critical judgment in evaluating eHealth information. Additionally, fostering a supportive and user-friendly online health information environment is essential. It is recommended that universities and colleges further establish good campus eHealth literacy learning and support channels. For example, good health information online platforms could be recommended on school websites, and in-person or virtual health information consultation could be applied within schools. These measures would collectively contribute to improving university students’ eHealth literacy, thereby encouraging their adoption of health-promoting lifestyles.
The author would like to thank Prof Silvia Wen-Yu Lee and Prof Shyh-Hsiang Lin for providing consultation and answering questions during the research process. The author would also like to thank Prof Yuan-Chin Chang and Prof Yi-Jia Lin for inspecting and confirming the translation accuracy and fluency of the Chinese eHealth Literacy Scale (eHEALS). In addition, the author thanks 6 experts and scholars, namely Dr Wen-Ting Huang, Dr Wei-Chen Li, Dr Chin-Yu Tsai, Dr Fang-Min Liu, Dr Chuan-Chun Stella Kuo, and Mr Hsueh-Wei Chen, for reviewing the content validity of eHEALS. The author also thanks all participating university students and 4 interviewers, namely Zi-Yu Peng, Tzu-Yin Lai, Ching-Sin Cheng, and You-Hsuan Yu, for their contribution to the study. Moreover, the author would like to thank Editage for English language editing. The paper-processing fee of publication was funded by PROZ Biotech CO, LTD. The study was not supported by other external funding.
The data sets generated and analyzed during this study are not publicly available but are available from the corresponding author upon reasonable request.
D-PC conceptualized and administered the study, analyzed and interpreted the results, and drafted and revised the manuscript. D-PC also reviewed and approved the final manuscript.
None declared.
The Chinese version of eHEALS. eHEALS: eHealth Literacy Scale.
The simplified version of Chinese HPLP. HPLP: health-promoting lifestyle profile.
Binary logistic regression for association of eHEALS with the HPLP dimensions (N=406). eHEALS: eHealth Literacy Scale; HPLP: health-promoting lifestyle profile.
average variance extracted |
confirmatory factor analysis |
comparative fit index |
composite reliability |
exploratory factor analysis |
eHealth Literacy Scale |
goodness-of-fit index |
health-promoting lifestyle profile |
incremental fit index |
normed fit index |
odds ratio |
relative fit index |
root mean square error of approximation |
standardized root mean square residual |
Tucker-Lewis index |
Taiwan Network Information Center |
variance inflation factor |
Edited by G Eysenbach, T de Azevedo Cardoso; submitted 30.08.23; peer-reviewed by R Moser; comments to author 03.11.23; revised version received 21.11.23; accepted 28.06.24; published 18.07.24.
©Dan-Ping Chao. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 18.07.2024.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
Historical record of indirect cost rates dating back to 1995.
Institutional Communications Bureau of Mines Building, Room 137 Laramie, WY 82071 Phone: (307) 766-2929 Email: [email protected]
Published July 17, 2024
The interim director of the University of Wyoming’s Literacy Research Center and Clinic (LRCC) has been selected as the center’s executive director.
Kim Gustafson, who has been interim director since July 2022, will begin her new role Aug. 1.
“Dr. Gustafson has excelled in collaborating with partners at UW, public schools across the state, government organizations and policymakers to implement the LRCC’s strategic plan,” says Jenna Shim, the John P. “Jack” Ellbogen Dean of UW’s College of Education. “Her efforts have already significantly impacted students throughout Wyoming, leveraging the LRCC’s talents and expertise, and we are looking forward to her continued success.”
As executive director, Gustafson will continue to focus on supporting K-12 students’ literacy growth through clinic support; empowering current K-12 teachers via professional development; and conducting research to advance literacy practices.
A longtime UW community member, Gustafson earned her bachelor’s degree in elementary education in 1998. She returned to UW and completed a master’s degree in educational leadership in 2003, followed by a Ph.D. in educational leadership in 2009.
After starting her career as an elementary classroom teacher, Gustafson began her role as an instructor in the School of Teacher Education in 2007. Her research interests include social studies and literacy integration in the elementary classroom, co-teaching, instructional leadership, teacher efficacy, school-university partnerships and mentoring pre-service teachers.
The College of Education will launch a search this fall for the inaugural Fisher Family Professor in Literacy.
The strange structures in a lava field reveal surprising details of Neolithic life.
Archaeologists recently discovered a whole mess of these circles—roughly 345, actually—in Saudi Arabia using aerial surveillance techniques. “These structures were individual dwellings, constructed in concentrations of varying numbers with associated domestic installations, such as hearths,” the research time behind the find, who published their study in Levant, explained. “The standing stone circle sites presented in this paper demonstrate a scale of Neolithic occupation not previously recognized in Saudi Arabia.”
Discovered in the Harrat al ‘Uwayrid lava field, the circles range in diameter from 13 to 26 feet, and all date to about 7,000 years ago. The team found evidence of stone walls and at least one doorway, and they believe the structures would have had roofs as well—either made from additional stones or other organic matter .
“Globally, early domestic architecture was always round, and rectangular houses only appear in the later Neolithic,” Jane McMahon, an honorary research fellow at the University of Western Australia and lead author of the paper, told Live Science .
The research team writes in the study that additional evidence found in the region supports a growing mix of human activity in the area during the time of the stone houses. Everything from the basalt stone tools to the animal remains found in the area indicated a mixed economy, supported by both domesticated and wild species and highlighted by the remains of sheep, goats, and cattle. The discovery of standing stone houses falls in line with similar ancient stone houses located in Jordan from roughly 500 years prior, showing a potential link between people from Jordan and those who lived in northwest Saudi Arabia.
Along with the stone houses, the team found rectangular structures made of stone. These have been dubbed mustatil—Arabic for rectangle —and the researchers believe that they may have been used for the sacrifice of cattle. According to the paper, it’s “likely that these two megalithic structure types are aspects of a single cultural entity.”
That entity likely pre-dated typical farming in a landscape , which wasn’t as dry at the time as the area is today. “There’s no evidence of farming domesticated species of plants like wheat and barley, but gathering wild plants likely took place,” McMahon told Live Science , “and perhaps manipulating the landscape to increase the likelihood and yield of wild species.”
Along with the bevy of stone, the area yielded seashells, believed to be from the Red Sea, which is roughly 75 miles away. That find suggests a developing network of trade and exchange that required mobility, giving an entirely fresh perspective on the rise of populations 7,000 years ago in northwest Saudi Arabia.
Tim Newcomb is a journalist based in the Pacific Northwest. He covers stadiums, sneakers, gear, infrastructure, and more for a variety of publications, including Popular Mechanics. His favorite interviews have included sit-downs with Roger Federer in Switzerland, Kobe Bryant in Los Angeles, and Tinker Hatfield in Portland.
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Recent graduate Holly Puza (B.A. ’24, Political Science, English Literature, International Studies, Certificate in European Studies) was awarded the 2024 Iwanter Prize for Undergraduate Research for her thesis, “Is That How Free Feels”: Aesthetic Knowledge in the Neo-Slave Narrative.
Additionally, recent graduate Matthew Masonius (B.A. ’24, Political Science and History, Certificates in Public Policy and Environmental Studies) was named Honorable Mention for the prize for his thesis, From ‘Great Society’ to ‘Good Government’: Watergate, the 1974 Elections, & the Ideological Evolution of the Democratic Party.
Learn more about their theses and the Iwanter Prize in the official press release for the award.
COMMENTS
Literature circles — a small group of students that gathers to discuss a book, much like a book club — are not a new idea , and in fact, remain quite popular because they are incredibly effective . Indeed, many studies of developing reading comprehension, including those by Harvard Graduate School of Education professor Catherine Snow ...
Research Base: Links & Resources: About the LCRC: for more information on literature circles, try these professional resources . Getting Started with Literature Circles (1999) Katherine Schlick Noe & Nancy J. Johnson. Literature Circles Resource Guide (2001)
Learning and teaching in WANDA Wiki wonderland: Literature circles in the digital commons. Teacher Librarian, 37, 2, 23-38. Noll, E. (1994). Social issues and literature circles with adolescents. Journal of Reading, 38, 2, 88-93. Peralta-Nash, C. (2003). Literature circles in a bilingual classroom: The power of language choice.
Thus, the authors identify and illustrate the potential of Literature Circles 2.0 in educating students with the capacity and. al citizens in today's multicultural world. knowledge they need to be successful glob-. ains and proposes anupdated approach to teaching reading and literacy to students from diverse educa-tional and cultural ...
Literature circles were first implemented in 1982 by Karen Smith, an elementary school teacher in Phoenix, Arizona. Handed a box of odd-and-end novels by a fellow teacher, Karen took them and promptly forgot about them. Later that year, some of her fifth grade students expressed an interest in reading them, organized themselves loosely into ...
Reason #3: Literature circles are fun, in part because they are social experiences. Students are expected to talk a lot, (in contrast to the rest of their time at school) to debate and argue their ideas. Students are invited to bring their experiences and feelings into the classroom and to share them. Reading has to be fun some of the time; if ...
The Research Literature Circles is an effective, proven strategy based on the principles of collaborative learning, independent reading and group discussion. This paper surveys and synthesizes the academic research related to Literature Circles and its components for the purpose of meeting the standards for research-based instruction as set ...
Overview. This lesson provides a basic introduction to literature circles, a collaborative and student-centered reading strategy. Students begin by selecting a book together then are introduced to the four jobs in the Literature Circles: Discussion Director, Literary Luminary, Vocabulary Enricher, and Checker. The teacher and student volunteers ...
Literature circles provide a way for students to engage in critical thinking and reflection as they read, discuss, and respond to books. Collaboration is at the heart of this approach. Students reshape and add onto their understanding as they construct meaning with other readers.
As the table shows, the amo unt of research c oncerning the ef fec ts of literature circles on reading ab ility has increased year by year. Four st udies were conducted in 2022, sh owing that more ...
text read, and improved social collaboration. With literature circles students are able to make several decisions on their own, which is motivating to many reluctant readers and gives students a feeling of control over. a part of their reading (Bums, 1998). First, students have a choice in the book they read.
Book Clubs. Literature circles and book clubs are similar in many ways: Lit circles and book clubs provide students with choices. Both provide opportunities for small group discussion. Both involve a variety of core texts in the classroom instead of a single novel or literary work. But there are some key differences.
Christ the King Christian School. Keywords. Middle level literature circles, collaborative learning. Abstract. The purpose of this action research project was to use literature circles to engage sixth. grade students when reading novels and responding to literature. Literature circles were. used to give the students more responsibility when ...
Action research is a form of research that involves the teacher and an investigation of his or her own classroom. Literature circles couple two potent ideas in education: independent reading and cooperative learning. Literature circles stem from the theory of holistic, or whole language, education.
Turk. Nebraska's Judith Turk, an assistant professor and co-coach of the university's Soil Judging Team, decided to put lit circles to the test in a dual undergraduate-graduate course on soil science.After being presented with reading assignments — chapters from edited books, a peer-reviewed journal article — students either watched a conventional lecture on those readings or took part ...
A literature circle is an activity in which . members meet to discuss and respond to . a book that they are all reading (Daniels 2002). As Cameron et al. (2012) explain, literature circles are led mostly by students, while the teacher remains in the background and performs only basic control functions. Roles are usually assigned to members of the
literature circles provide students opportunities to critically analyze literature while collaborating with others in an interactive format. Implementation, formats, resources, and assessments to infuse ... (Prensky, 2001). Research has found that many students spend about nine hours a day online chatting, blogging, watching YouTube videos, or ...
What Is A Literature Circle? by Terry Heick. Literature Circles are a way for students to assume a specific role in the study of something (usually a text). Though almost always associated with the content area of 'Literature' or 'Language Arts' in North America, the concept of studying a topic in groups by assigning functional roles for each group member can be applied in the study of ...
Keywords: Reading education, Reading comprehension, Literature circles, Book review, Prospective teacher, Reading desire. 1. Introduction. As is the case in all walks of life, in education the diversification and change of the tools, methods, and techniques used are inevitable as well.
Literature circles use the student role of Literary Luminary as opportunity for students to look at. quotes, details, sections of text, and passages that are crucial for the reader to focus on as well as. analyze to deepen their understanding. According to Marchiando (2013), "Literary luminaries.
The Literature Circles Resource Guide provides the practical support you need to make literature circles succeed. The Resource Guide offers suggestions for your instructional planning, as well as forms you can photocopy for students. In addition, the accompanying CD-ROM contains all of the forms and teaching guidelines formatted for Mac and PC ...
ABSTRACT. This synthesis reviews four studies which explore the relationship between Literature Circles, a peer-led collaborative learning strategy, and students' spoken and written responses to literature, attempting to evaluate the effects Literature Circles have on reading comprehension. The studies referenced herein reveal that the ...
The group grade can be based on group assignments and activities from literature circle meetings. You can use the group grade as the basis for adjusting individual gradesfor each student. These adjustments can be based on their performance during their literature circle roles. It can also include peer feedback from peer evaluation forms.
Background: The popularization of the internet and rapid development of mobile devices have led to an increased inclination and opportunities to obtain health-related information online. The eHealth Literacy Scale (eHEALS), widely used for measuring eHealth literacy, assesses an individual's ability to search, understand, appraise, and use eHealth information.
Office of Research Services. 215-898-7293. [email protected]. 3451 Walnut Street 5th floor, Franklin Building, Philadelphia PA 19104-6205 ©2020 Office of Research Services at the University of Pennsylvania ...
A book that discusses the importance of a new social contract for education and how it can help communities flourish together.
The interim director of the University of Wyoming's Literacy Research Center and Clinic (LRCC) has been selected as the center's executive director. Kim Gustafson, who has been interim director since July 2022, will begin her new role Aug. 1. "Dr. Gustafson has excelled in collaborating with partners at UW, public schools across the state ...
New research in Saudi Arabia unveils 345 stone circles, believed to be 7,000-year-old homes, shedding light on Neolithic settlements and early human lifestyles.
Established firms are increasingly finding avenues of collaboration and engagement with startup firms. For these organizations, corporate accelerator programs (CA) are increasingly becoming important vehicles in pursuing innovation and the need to stay relevant through corporate-startup engagement. On the other hand, startups also benefit significantly from these short-term, fast-paced ...
Recent graduate Holly Puza (B.A. '24, Political Science, English Literature, International Studies, Certificate in European Studies) was awarded the 2024 Iwanter Prize for Undergraduate Research for her thesis, "Is That How Free Feels": Aesthetic Knowledge in the Neo-Slave Narrative. Additionally, recent graduate Matthew Masonius (B.A. '24, Political Science and History, Certificates ...